Alzheimer's Disease

Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network.

Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitatin...

A ResNet mini architecture for brain age prediction.

The brain presents age-related structural and functional changes in the human life, with different e...

CKG-IMC: An inductive matrix completion method enhanced by CKG and GNN for Alzheimer's disease compound-protein interactions prediction.

Alzheimer's disease (AD) is one of the most prevalent chronic neurodegenerative disorders globally, ...

Making robots matter in dementia care: Conceptualising the triadic interaction between caregiver, resident and robot animal.

While previous research studies have focused on either caregivers' or residents' perception and use ...

Dementia and AI.

Robot-based solution for helping Alzheimer patients.

Alzheimer's is a progressive and debilitating neurological disorder characterized by cognitive decli...

Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.

In this study, our objective was to assess the performance of two deep learning-based hippocampal se...

Pain prediction model based on machine learning and SHAP values for elders with dementia in Taiwan.

INTRODUCTION: Pain conditions are common in elderly individuals, including those with dementia. Howe...

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for dis...

Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer's Disease Using 3D Comprehensive Visual Stimuli.

Alzheimer's Disease (AD) is a neurodegenerative disorder that causes a continuous decline in cogniti...

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. Howev...

Exploring inertial sensor-based balance biomarkers for early detection of mild cognitive impairment.

Dementia is characterized by a progressive loss of cognitive abilities, and diagnosing its early sta...

Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features.

To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective in...

Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.

OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the patho...

Union is strength: the combination of radiomics features and 3D-deep learning in a sole model increases diagnostic accuracy in demented patients: a whole brain 18FDG PET-CT analysis.

OBJECTIVE: FDG PET imaging plays a crucial role in the evaluation of demented patients by assessing ...

PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies.

Despite the abundance of genotype-phenotype association studies, the resulting association outcomes ...

A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases.

BACKGROUND AND AIMS: A machine learning algorithm based on circulating metabolic biomarkers for the ...

Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence.

Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating s...

Positive Emotional Responses to Socially Assistive Robots in People With Dementia: Pilot Study.

BACKGROUND: Interventions and care that can evoke positive emotions and reduce apathy or agitation a...

Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning.

Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's ...

Performance Evaluation of Deep, Shallow and Ensemble Machine Learning Methods for the Automated Classification of Alzheimer's Disease.

Artificial intelligence (AI)-based approaches are crucial in computer-aided diagnosis (CAD) for vari...